• DocumentCode
    1795840
  • Title

    Cluster restarted differential migration

  • Author

    Dlapa, Marek

  • Author_Institution
    Fac. of Appl. Inf., Tomas Bata Univ. in Zlin, Zlin, Czech Republic
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    151
  • Lastpage
    159
  • Abstract
    The paper deals with a new evolutionary algorithm - Differential Migration, and provides comparison with other algorithms of this type. Cluster Restarted Differential Migration is examined with standard benchmark test functions for performance comparison. Standard Differential Migration and Restart Covariance Matrix Adaptation Evolution Strategy With Increasing Population Size (IPOP-CMA-ES) are used as reference and the results are compared with Cluster Restarted Differential Migration. The main feature of the algorithm is the fact that it is a generalization of SOMA (Self-Organizing Migration Algorithm) giving a general scheme incorporating both strategies of SOMA, i.e. all-to-one and all-to-all, into one general algorithm using clusters and a parameter specifying the measure of trade-off between all-to-one and all-to-all strategy. Besides this, some principles from Differential Evolution are adopted implying higher speed of search than SOMA for most of benchmarks and real-world applications. In this paper, Cluster Restarted Differential Migration is presented providing some new features compared to its standard form.
  • Keywords
    covariance matrices; evolutionary computation; swarm intelligence; IPOP-CMA-ES; SOMA; cluster restarted differential migration; differential evolution; evolutionary algorithm; restart covariance matrix adaptation evolution strategy with increasing population size; self-organizing migration algorithm; Algorithm design and analysis; Benchmark testing; Clustering algorithms; Cost function; Sociology; Statistics; Vectors; IPOP-CMA-ES; SOMA; evolutionary computation; memetic algorithms; swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Foundations of Computational Intelligence (FOCI), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/FOCI.2014.7007820
  • Filename
    7007820